Age and sex dependency of thoracic aortopathy in a mouse model of Marfan syndrome

Thoracic aortic aneurysm is one of the manifestations of Marfan syndrome (MFS) that is known to affect men more severely than women. However, the incidence of MFS is similar between men and women. The aim of this study is to show that during pathological aortic dilation, sex-dependent severity of thoracic aortopathy in a mouse model of MFS translates into sex-dependent alterations in cells and matrix of the ascending aorta, consequently affecting aortic biomechanics. Fibrillin-1 C1041G/+ (Het) mice were used as a mouse model of MFS. Ultrasound measurements from 3 to 12 mo showed increased aortic diameter in Het aorta, with larger percentage increase in diameter for males compared with females. Immunohistochemistry showed decreased contractile smooth muscle cells in Het aortic wall compared with healthy aorta, which was accompanied by decreased contractility measured by wire myography. Elastin autofluorescence, second-harmonic generation microscopy of collagen fibers, and passive biomechanical assessments using myography showed more severe damage to elastin fibers, increased medial fibrosis, and increased stiffness of the aortic wall in MFS males but not females. Male and female Het mice showed increased expression of Sca-1-positive adventitial progenitor cells versus controls at young ages. In agreement with clinical data, Het mice demonstrate sex-dependent severity of thoracic aortopathy. It was also shown that aging exacerbates the disease state especially for males. Our findings suggest that female mice are protected from progression of aortic dilation at early ages, leading to a lag in aneurysm growth.NEW & NOTEWORTHY Male Fbn1^C1041G/+ mice show more severe thoracic aortic changes compared with females, especially at 12 mo of age. Up to 6 mo of age, Sca-1⁺ smooth muscle progenitor cells are more abundant in the adventitia of both male and female Fbn1 Het mice compared with wild types (WTs). Male and female Het mice show similar patterns of expression of Sca-1⁺ cells at early ages.

Molecular simulation study of the competitive adsorption of H2O and CO2 in zeolite 13X

The presence of H2O in postcombustion gas streams is an important technical issue for deploying CO2-selective adsorbents. Because of its permanent dipole, H2O can interact strongly with materials where the selectivity for CO2 is a consequence of its quadrupole interacting with charges in the material. We performed molecular simulations to model the adsorption of pure H2O and CO2 as well as H2O/CO2 mixtures in 13X, a popular zeolite for CO2 capture processes that is commercially available. The simulations show that H2O reduces the capacity of these materials for adsorbing CO2 by an order of magnitude and that at the partial pressures of H2O relevant for postcombustion capture, 13X will be essentially saturated with H2O .

Mapping of Functional Groups in Metal-Organic Frameworks

We determined the heterogeneous mesoscale spatial apportionment of functional groups in a series of multivariate metal-organic frameworks (MTV-MOF-5) containing BDC (1,4-benzenedicarboxylate) linkers with different functional groups—B (BDC-NH2), E (BDC-NO2), F [(BDC-(CH3)2], H [BDC-(OC3H5)2], and I [BDC-(OC7H7)2]—using solid-state nuclear magnetic resonance measurements combined with molecular simulations. Our analysis reveals that these methods discern between random (EF), alternating (EI and EHI), and various cluster (BF) forms of functional group apportionments. This combined synthetic, characterization, and computational approach predicts the adsorptive properties of crystalline MTV-MOF systems. This methodology, developed in the context of ordered frameworks, is a first step in resolving the more general problem of spatial disorder in other ordered materials, including mesoporous materials, functionalized polymers, and defect distributions within crystalline solids.

Similarity-driven discovery of zeolite materials for adsorption-based separations

Crystalline porous materials can be exploited in many applications. Discovery of materials with optimum adsorption properties typically involves expensive brute-force characterization of large sets of materials. An alternative approach based on similarity searching that enables discovery of materials with optimum adsorption for CO(2) and other molecules at a fraction of the cost of brute-force characterization is demonstrated.

Large-scale computational screening of zeolites for ethane/ethene separation

Large-scale computational screening of thirty thousand zeolite structures was conducted to find optimal structures for separation of ethane/ethene mixtures. Efficient grand canonical Monte Carlo (GCMC) simulations were performed with graphics processing units (GPUs) to obtain pure component adsorption isotherms for both ethane and ethene. We have utilized the ideal adsorbed solution theory (IAST) to obtain the mixture isotherms, which were used to evaluate the performance of each zeolite structure based on its working capacity and selectivity. In our analysis, we have determined that specific arrangements of zeolite framework atoms create sites for the preferential adsorption of ethane over ethene. The majority of optimum separation materials can be identified by utilizing this knowledge and screening structures for the presence of this feature will enable the efficient selection of promising candidate materials for ethane/ethene separation prior to performing molecular simulations.

In silico screening of carbon-capture materials

One of the main bottlenecks to deploying large-scale carbon dioxide capture and storage (CCS) in power plants is the energy required to separate the CO(2) from flue gas. For example, near-term CCS technology applied to coal-fired power plants is projected to reduce the net output of the plant by some 30% and to increase the cost of electricity by 60-80%. Developing capture materials and processes that reduce the parasitic energy imposed by CCS is therefore an important area of research. We have developed a computational approach to rank adsorbents for their performance in CCS. Using this analysis, we have screened hundreds of thousands of zeolite and zeolitic imidazolate framework structures and identified many different structures that have the potential to reduce the parasitic energy of CCS by 30-40% compared with near-term technologies.